Polymer‐encapsulated engineered adult mesenchymal stem cells secrete exogenously regulated rhBMP‐2, and induce osteogenic and angiogenic tissue formation
Bibliographic record
Abstract
Abstract We have previously shown that genetically engineered adult mesenchymal stem cells (AMSCs) expressing recombinant human bone morphogenetic protein –2 (rhBMP‐2), under tet‐regulation, can induce bone formation and regeneration. We showed that these cells induce bone formation via paracrine and autocrine effect of the secreted rhBMP‐2 protein. To distinguish between these two effects, and to develop a platform for continuous delivery of rhBMP‐2 by engineered cells protected from the immune system, we have used hydrogel polymer (alginate) in order to encapsulate the AMSCs. Mixing of the cells with potassium alginate, followed by sedimentation in Ca2+ solution, results in polymerization of the alginate around the cells, forming microcapsules composed of a membrane allowing diffusion of small molecule and proteins. Encapsulated engineered AMSCs were able to survive inside the capsules in vitro and in vivo and secrete rhBMP‐2 under tet‐regulation. Transplantation of capsules both subcutaneously and into bone defect elicited physiological response manifested in osteogenic tissue composed of bone trabeculae and cartilage. Inside the capsules, engineered AMSCs differentiated to chondrocytes (autocrine effect), but not to osteoblasts. Newly formed bone has developed around the polymeric external layer without any observed intermediate layer of tissue. There was no evidence of immune response in the transplants area. We therefore conclude that engineered AMSCs can be efficiently encapsulated within polymeric alginate microcapsules, maintain viability, differentiate by autocrine effect, secrete rhBMP‐2 under exogenous regulation, and induce bone formation by paracrine effect, with no adverse or immune response to the transplanted capsules. Copyright © 2003 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".